Cine cardiac magnetic resonance imaging (MRI) is widely used for the diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As compared to computed tomography (CT), MRI, however, requires a long scan time, which inevitably induces motion artifacts and causes patients' discomfort. Thus, there has been a strong clinical motivation to develop techniques to reduce both the scan time and motion artifacts. Given its successful applications in other medical imaging tasks such as MRI super-resolution and CT metal artifact reduction, deep learning is a promising approach for cardiac MRI motion artifact reduction. In this paper, we propose a novel recurrent generative adversarial network model for cardiac MRI motion artifact reduction. This model utilizes bi-directional convolutional long short-term memory (ConvLSTM) and multi-scale convolutions to improve the performance of the proposed network, in which bi-directional ConvLSTMs handle long-range temporal features while multi-scale convolutions gather both local and global features. We demonstrate a decent generalizability of the proposed method thanks to the novel architecture of our deep network that captures the essential relationship of cardiovascular dynamics. Indeed, our extensive experiments show that our method achieves better image quality for cine cardiac MRI images than existing state-of-the-art methods. In addition, our method can generate reliable missing intermediate frames based on their adjacent frames, improving the temporal resolution of cine cardiac MRI sequences.

Background and Purpose—: Cervicocerebral vascular calcification on computed tomography angiography is a known sign of advanced atherosclerosis. However, the clinical significance of calcification pattern remains unclear. In this study, we aimed to investigate the potential association between spotty calcium and acute ischemic stroke. Methods—: This study included patients with first-time nonlacunar ischemic stroke (N=50) confirmed by brain magnetic resonance imaging or nonenhanced head computed tomography, as well as control subjects with asymptomatic carotid atherosclerosis (N=50) confirmed by carotid ultrasonography. Subjects in both groups underwent contrast-enhanced cervicocerebral computed tomography angiography within a week after the initial imaging examination. Spotty calcification was evaluated at 11 arterial segments commonly affected by atherosclerosis along the carotid and vertebrobasilar circulation. Statistical analysis was performed comparing the frequency and spatial pattern of spotty calcification between the 2 groups. Results—: Spotty calcification in the Stroke group was markedly more prevalent than that in the Control group (total SC count: 8.74±4.96 versus 1.84±1.82, P <0.001). The odds ratio (95% CI) for stroke was 2.49 (1.55–4.00) for spotty calcification at bilateral carotid bifurcation, 1.52 (1.13–2.04) at carotid siphon, and 1.98 (1.45–2.69) at all evaluated locations. A total number of 3 spotty calcifications were determined as the optimal cutoff threshold for increased risk of stroke. Spotty calcium showed significantly greater area under the receiver operating characteristics curve than total calcium volume irrespective of size (0.88 versus 0.77). Within the Stroke group, ipsilateral lateral side showed significantly more spotty calcium than the contralateral side (5.18±3.05 versus 3.56±2.67, P <0.001). Conclusions—: Nonlacunar ischemia stroke was associated with markedly increased incidence of spotty calcification with a distinct spatial pattern on cervicocerebral computed tomography compared with subclinical atherosclerosis, suggesting the potential role of spotty calcification for improving the risk stratification for ischemic stroke.

Previous studies have linked cardiac dysfunction to loss of metabolites in the creatine kinase system. Chemical exchange saturation transfer (CEST) is a promising metabolic cardiovascular magnetic resonance (CMR) imaging technique and has been applied in the heart for creatine mapping. However, current limitations include: (a) long scan time, (b) residual cardiac and respiratory motion, and (c) B0 field variations induced by respiratory motion. An improved CEST CMR technique was developed to address these problems. Animals with chronic myocardial infarction (N = 15) were scanned using the proposed CEST CMR technique and a late gadolinium enhancement (LGE) sequence as reference. The major improvements of the CEST CMR technique are: (a) Images were acquired by single-shot FLASH, significantly increasing the scan efficiency. (b) All images were registered to reduce the residual motion. (c) The acquired Z-spectrum was analyzed using 3-pool-model Lorentzian-line fitting to generate CEST signal, reducing the impact of B0 field shifting due to respiratory motion. Feasibility of the technique was tested in a porcine model with chronic myocardial infarction. CEST signal was measured in the scar, border zone and remote myocardium. Initial studies were performed in one patient. In all animals, healthy remote myocardial CEST signal was elevated (0.16 ± 0.02) compared to infarct CEST signal (0.09 ± 0.02, P < 0.001) and the border zone (0.12 ± 0.02, P < 0.001). For both animal and patient studies, the hypointense regions in the CEST contrast maps closely match the bright areas in the LGE images. The proposed CEST CMR technique was developed to address long scan times, respiratory and cardiac motion, and B0 field variations. Lower CEST signal in bright region of the LGE image is consistent with the fact that myocardial infarction has reduced metabolic activity.

Lee SE, et al. Korean Circ J. 2018 Aug;49:e13. https://doi.org/10.4070/kcj.2018.0246